Fix categorical hue data swapped in split violinplot#3966
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With pandas 3.0 and CategoricalDtype hue columns, groupby(..., sort=False, observed=False).get_group(key) matches groups by category code rather than by label value. This causes iter_data to yield data belonging to the wrong hue group when the first-appearance order in the data differs from the category order. Changing observed=False to observed=True fixes the lookup. Unobserved category combinations are still handled correctly because iter_data already catches KeyError and returns an empty DataFrame for missing groups. Closes mwaskom#3893
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Fixes #3893.
With pandas 3.0 and a CategoricalDtype hue column,
groupby(..., sort=False, observed=False).get_group(key)matches groups by category code rather than by label value. This causesiter_datato yield data belonging to the wrong hue group when the first-appearance order in the data differs from the category order - resulting in swapped violins in split violin plots.The fix changes
observed=Falsetoobserved=Truein theiter_datagroupby call. This is safe because:observed=Falsewas only added in 9049ddd to silence a pandas FutureWarning - the original code used the default (which wasTruein older pandas).True.iter_dataalready handles missing groups via the existingKeyErrorcatch, so unobserved category combinations still produce empty DataFrames as expected.Includes a regression test that verifies the correct hue group data is assigned to each violin half.